KNOWLEDGE-BASED IMAGE-ANALYSIS FOR GEOPHYSICAL INTERPRETATION

Geophysical seismic interpretation is part of geophysical oil prospecting. It evaluates and analyses seismic reflection data, aiming at the detection of the position of hydrocarbon reservoirs. This paper provides a review of current efforts to automate, at least partially, seismic interpretation. As will be shown, this research area is very active and is a melting pot of various different approaches and techniques: artificial intelligence, pattern recognition, image processing, graphics, fuzzy set theory and, of course, geophysics and geology. Some methods of seismic pattern recognition (e.g. remote correlation, fuzzy seismic modeling, recognition of reservoir boundaries) and of seismic image processing (horizon following, texture analysis) are presented and some applications are shown. Expert systems used in geophysical interpretation (mainly in well log interpretation) are also briefly described. Finally, an automated system for knowledge-based image analysis for geophysical interpretation is dicussed. Its low-level vision techniques, its knowledge representation, and the control strategy for seismic pattern search are described.